Correlates of sleep variability in a mobile EEG-based volunteer study.
BSETS
Mobile EEG
Multiday observational study
Sleep regularity index
Sleep variability
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
29 10 2024
29 10 2024
Historique:
received:
16
08
2024
accepted:
10
10
2024
medline:
30
10
2024
pubmed:
30
10
2024
entrez:
30
10
2024
Statut:
epublish
Résumé
Variable sleep patterns are a risk factor for disease, but the reasons some people express greater within-individual variability of sleep characteristics remains poorly understood. In our study, we leverage BSETS, a novel mobile EEG-based dataset in which 1901 nights in total were recorded from 267 extensively phenotyped participants to identify factors related to demographics, mental health, personality, chronotype and sleep characteristics which predict variability in sleep, including detailed sleep macrostructure metrics. Young age, late chronotype, and napping emerged as robust correlates of increased sleep variability. Correlations with other characteristics (such as student status, personality, mental health and co-sleeping) generally disappeared after controlling for age. We critically examine the utility of controlling the correlates of sleep variability for the means of sleep variables. Our research shows that age and sleep habits affecting the amount of sleep pressure at night are the most important factors underlying sleep variability, with a smaller role of other psychosocial variables. The avoidance of daytime naps emerges as the most promising modifiable behavior associated with increased sleep regularity.
Identifiants
pubmed: 39472477
doi: 10.1038/s41598-024-76117-2
pii: 10.1038/s41598-024-76117-2
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
26012Subventions
Organisme : Magyar Tudományos Akadémia
ID : János Bolyai Research Scholarship
Organisme : Nemzeti Kutatási Fejlesztési és Innovációs Hivatal
ID : 138935
Organisme : Ministry of Culture and Innovation in Hungary
ID : TKP2021-EGA-25
Informations de copyright
© 2024. The Author(s).
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